Feature Extraction
Transformers
PyTorch
hubert
Inference Endpoints
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@@ -149,9 +149,9 @@ Training employs a two-level language, data source up-sampling during training.
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  * Faiss index for continuous pre-training (OPQ16_64,IVF1000_HNSW32,PQ16x4fsr).
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  **Related Models:**
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- * [Third Iteration repository](https://huggingface.co/utter-project/mHuBERT-147)
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- * [Second Iteration repository](https://huggingface.co/utter-project/mHuBERT-147-base-2nd-iter)
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- * [CommonVoice Prototype (12 languages)](https://huggingface.co/utter-project/hutter-12-3rd-base)
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  # Training
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  * Faiss index for continuous pre-training (OPQ16_64,IVF1000_HNSW32,PQ16x4fsr).
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  **Related Models:**
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+ * [Third Iteration mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147)
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+ * [Second Iteration mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147-base-2nd-iter)
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+ * [HUTTER-12 CommonVoice Prototype (12 languages)](https://huggingface.co/utter-project/hutter-12-3rd-base)
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  # Training
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